Raw cotton yield
Raw cotton yield in Russia, the Southern Federal District, and the Volgograd Oblast is broken down by various farm types. Rows are categorized by territory and farm type, allowing comparison of individual regions and specific producer groups with the national average. Columns contain data for different periods, including the percentage ratio of 2022 figures to 2021
Chart of raw cotton yield in Russia, the Southern Federal District, and the Volgograd Oblast
Set in numbers
The table is a snapshot — 4 series shown across 5 breakdowns. 13 values in total.
“Российская Федерация / ... / ...” leads the table with 148, “North Caucasus Federal District / ... / ..” closes it with 3. The gap between them is 49.4-fold.
All table numbers are series: 4
| Series | Хозяйства населения | Крестьянские (фермерские) хозяйства и индивидуальные предприниматели | 2022 | 2021 | 2022 в % к 2021 |
|---|---|---|---|---|---|
| Российская Федерация / ... / ... | — | 20,00 | 21,04 | 14,20 | 148,17 |
| Южный федеральный округ | — | 20,00 | 20,00 | 17,00 | 117,65 |
| Волгоградская область | — | 20,00 | 20,00 | 17,00 | 117,65 |
| Северо-Кавказский федеральный округ / ... / ... | — | — | — | 3,00 | — |
How to read this table
Comparing different farm scales shows the difference in production efficiency between large-scale enterprises and small-scale farmers. The table includes separate rows for the Russian Federation, the Southern Federal District, and the Volgograd Oblast. This helps to understand the share of yield for a specific region or district relative to national values
What is visible in these numbers
Only 65% of the cells carry a value — empty cells are missing in the source publication and are not filled in here.
The same indicator in other breakdowns (3)
More in the section Bulletins on the state of agriculture (electronic versions)»
Period and application
Data is published in electronic versions of agricultural bulletins. Information includes data on household farms, peasant and farm enterprises, and individual entrepreneurs. The data is relevant for agribusiness specialists and those analyzing crop production efficiency in the country's southern regions
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